The public assistance system is supposed to offer a bridge between poverty and self-sufficiency. Families receive benefits such as Temporary Assistance for Needy Families (TANF) or Supplemental Nutrition Assistance Program (SNAP) to soften the impact of loss of income. The programs are intended to be limited in duration and provide a very modest amount of financial support. Some families are fortunate to also receive a housing voucher or a child care subsidy to help offset basic expenses. Eligibility for benefits varies by program and is based on different criteria, most of which are linked to personal income. This study asks: what happens when benefits are cut before individuals reach economic stability? This is frequently called the “benefits cliff.”

A hierarchical production planning structure enables manufacturing systems to handle customer
disturbances with different measures on different planning levels. Two different kinds of customer order
behavior can be observed and are as well discussed in literature.

Modelling real workforce choices accurately via Agent Based Models and System Dynamics requires
input data on the actual preferences of individual agents. Often lack of data means that analysts can have
an understanding of how agents move through the system, but not why, and when.

Hybrid simulation, the combination of simulation paradigms to address a problem is becoming more popular as the problems we are presented with become more complex. This is evidenced by an increase in the number of hybrid papers published in specific domains and the number of hybrid simulation frameworks being produced across domains.

All over the world, and in particular in Germany, a trend toward a more sustainable electric energy supply
including energy efficiency and climate protection can be observed. Simulation models can support these
energy transitions by providing beneficial insights for the development of different electricity generation mix
strategies in future electric energy systems.

Various actors are involved in hinterland transportation of incoming rail containers along the maritime transport chain. To coordinate each actor’s logistics processes, and therefore to improve utilization of existing transport capacity, the early provision of information, e.g. in form of estimated time of arrival (ETA), is inevitable.

Economic slowdown and construction demand shrinkage reduces the profit backlog for construction contractors and bites into their profit margin. The resulting fierce competition for jobs forces construction companies to look for more sophisticated analytical tools to analyze and improve their bidding strategies. For each contractor, bidding strategy is a decision-making process that is driven by the firm’s financial goals with the final objective of maximizing the firm’s gross profit and surpassing the breakeven point. This paper proposes a methodology to model and analyze different bidding strategies with hybrid agent based-system dynamics (ABSD) simulation.

The desire to better understand the transmission of infectious disease in the real world has motivated the representation of epidemic diffusion in the context of quantitative simulation. In recent decades, both individual-based (such as Agent-Based) models and aggregate models (such as System Dynamics) are widely used in epidemiological modeling. This paper compares the difference between system dynamics models and agent-based models in the context of Tuberculosis (TB) transmission, considering smoking as a risk factor.

Healthcare simulation models have attracted significant offered important insights in to health policy selection. More complete accounting for the cost and health implications of upstream interventions is hindered by the need to consider impact on, and interactions between, multiple comorbidities. Within this paper, we explore several distinct approaches for representing comorbidities, some of them at the aggregate level, and some of them at the individual level. All of these representations have the virtue of being declarative, in that they allow the user to focus on what is to be characterized, rather than how it is to be implemented. Our exploration suggests that while several aggregate representations of comorbidities are possible, they suffer from a variety of shortcomings, ranging from low fidelity to combinatorial blowup. While individual-level representations impose a heavy performance load, greater difficulties in calibration and less rapid analysis, such representations do offer greater transparency, modifiability, scalability, and modularity, and ease of representing transmission and influence networks. With much to recommend each approach, further research is needed to shed additional light on the tradeoffs and identify situations where one representation is preferable to another.